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Bayesian Treed Gaussian Process Models With an Application to Computer Modeling

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Cited by:

  1. Matthew W. Wheeler, 2019. "Bayesian additive adaptive basis tensor product models for modeling high dimensional surfaces: an application to high‐throughput toxicity testing," Biometrics, The International Biometric Society, vol. 75(1), pages 193-201, March.
  2. Maria Masotti & Lin Zhang & Ethan Leng & Gregory J. Metzger & Joseph S. Koopmeiners, 2023. "A novel Bayesian functional spatial partitioning method with application to prostate cancer lesion detection using MRI," Biometrics, The International Biometric Society, vol. 79(2), pages 604-615, June.
  3. Monterrubio-Gómez, Karla & Roininen, Lassi & Wade, Sara & Damoulas, Theodoros & Girolami, Mark, 2020. "Posterior inference for sparse hierarchical non-stationary models," Computational Statistics & Data Analysis, Elsevier, vol. 148(C).
  4. MacDonald, Blake & Ranjan, Pritam & Chipman, Hugh, 2015. "GPfit: An R Package for Fitting a Gaussian Process Model to Deterministic Simulator Outputs," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i12).
  5. Paulo, Rui & García-Donato, Gonzalo & Palomo, Jesús, 2012. "Calibration of computer models with multivariate output," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3959-3974.
  6. Storlie, Curtis B. & Reich, Brian J. & Helton, Jon C. & Swiler, Laura P. & Sallaberry, Cedric J., 2013. "Analysis of computationally demanding models with continuous and categorical inputs," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 30-41.
  7. Paciorek, Christopher J. & Lipshitz, Benjamin & Zhuo, Wei & Prabhat, . & Kaufman, Cari G. G. & Thomas, Rollin C., 2015. "Parallelizing Gaussian Process Calculations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i10).
  8. Matthew Plumlee, 2014. "Fast Prediction of Deterministic Functions Using Sparse Grid Experimental Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1581-1591, December.
  9. Fadel Hamid Hadi ALHUSSEINI, 2017. "Selection Of Variables Influencing Iraqi Banks Deposits By Using New Bayesian Lasso Quantile Regression," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 6(1), pages 46-59, JULY.
  10. Marco H. Benedetti & Veronica J. Berrocal & Naveen N. Narisetty, 2022. "Identifying regions of inhomogeneities in spatial processes via an M‐RA and mixture priors," Biometrics, The International Biometric Society, vol. 78(2), pages 798-811, June.
  11. Kleijnen, J.P.C., 2009. "Sensitivity Analysis of Simulation Models," Other publications TiSEM 2016cf94-0329-4aa0-a4ea-4, Tilburg University, School of Economics and Management.
  12. Kelly R. Moran & Matthew W. Wheeler, 2022. "Fast increased fidelity samplers for approximate Bayesian Gaussian process regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1198-1228, September.
  13. Cole, D. Austin & Gramacy, Robert B. & Ludkovski, Mike, 2022. "Large-scale local surrogate modeling of stochastic simulation experiments," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
  14. Jing Chang & Herbert K.H. Lee, 2015. "Variable selection via a multi-stage strategy," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(4), pages 762-774, April.
  15. Isabelle Grenier & Bruno Sansó & Jessica L. Matthews, 2024. "Multivariate nearest‐neighbors Gaussian processes with random covariance matrices," Environmetrics, John Wiley & Sons, Ltd., vol. 35(3), May.
  16. Matthias Katzfuss, 2017. "A Multi-Resolution Approximation for Massive Spatial Datasets," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 201-214, January.
  17. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
  18. Peter Müeller & Fernando A. Quintana & Garritt Page, 2018. "Nonparametric Bayesian inference in applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 175-206, June.
  19. Davis, Casey B. & Hans, Christopher M. & Santner, Thomas J., 2021. "Prediction of non-stationary response functions using a Bayesian composite Gaussian process," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
  20. Fadel Hamid Hadi Alhusseini & Taha al Shaybawee & Fedaa Abd Almajid Sabbar Alaraje, 2017. "Identify Relative importance of covariates in Bayesian lasso quantile regression via new algorithm in statistical program R," Romanian Statistical Review, Romanian Statistical Review, vol. 65(4), pages 99-110, December.
  21. Ning Zhang & Daniel W. Apley, 2016. "Brownian Integrated Covariance Functions for Gaussian Process Modeling: Sigmoidal Versus Localized Basis Functions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1182-1195, July.
  22. Sigal Levy & David Steinberg, 2010. "Computer experiments: a review," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(4), pages 311-324, December.
  23. Maia, Mateus & Murphy, Keefe & Parnell, Andrew C., 2024. "GP-BART: A novel Bayesian additive regression trees approach using Gaussian processes," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
  24. Pulong Ma & Georgios Karagiannis & Bledar A. Konomi & Taylor G. Asher & Gabriel R. Toro & Andrew T. Cox, 2022. "Multifidelity computer model emulation with high‐dimensional output: An application to storm surge," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 861-883, August.
  25. Bozağaç, Doruk & Batmaz, İnci & Oğuztüzün, Halit, 2016. "Dynamic simulation metamodeling using MARS: A case of radar simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 124(C), pages 69-86.
  26. Daniel W. Gladish & Daniel E. Pagendam & Luk J. M. Peeters & Petra M. Kuhnert & Jai Vaze, 2018. "Emulation Engines: Choice and Quantification of Uncertainty for Complex Hydrological Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(1), pages 39-62, March.
  27. Yi Liu & Veronika Ročková & Yuexi Wang, 2021. "Variable selection with ABC Bayesian forests," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 453-481, July.
  28. Bledar A. Konomi & Georgios Karagiannis & Kevin Lai & Guang Lin, 2017. "Bayesian Treed Calibration: An Application to Carbon Capture With AX Sorbent," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 37-53, January.
  29. Zhou Lan & Brian J. Reich & Joseph Guinness & Dipankar Bandyopadhyay & Liangsuo Ma & F. Gerard Moeller, 2022. "Geostatistical modeling of positive‐definite matrices: An application to diffusion tensor imaging," Biometrics, The International Biometric Society, vol. 78(2), pages 548-559, June.
  30. Nick Terry & Youngjun Choe, 2021. "Splitting Gaussian processes for computationally-efficient regression," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-17, August.
  31. Lian, Heng & Li, Gaorong, 2014. "Series expansion for functional sufficient dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 150-165.
  32. Andrew Hoegh & Marco A. R. Ferreira & Scotland Leman, 2016. "Spatiotemporal model fusion: multiscale modelling of civil unrest," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 529-545, August.
  33. Horiguchi, Akira & Pratola, Matthew T. & Santner, Thomas J., 2021. "Assessing variable activity for Bayesian regression trees," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
  34. Grant Hutchings & Bruno Sansó & James Gattiker & Devin Francom & Donatella Pasqualini, 2023. "Comparing emulation methods for a high‐resolution storm surge model," Environmetrics, John Wiley & Sons, Ltd., vol. 34(3), May.
  35. Samuel W. Malone & Robert B. Gramacy & Enrique Ter Horst, 2016. "Timing Foreign Exchange Markets," Econometrics, MDPI, vol. 4(1), pages 1-23, March.
  36. Scott, James G., 2012. "Benchmarking historical corporate performance," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1795-1807.
  37. Huo, Jinbiao & Liu, Zhiyuan & Chen, Jingxu & Cheng, Qixiu & Meng, Qiang, 2023. "Bayesian optimization for congestion pricing problems: A general framework and its instability," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 1-28.
  38. Erickson, Collin B. & Ankenman, Bruce E. & Sanchez, Susan M., 2018. "Comparison of Gaussian process modeling software," European Journal of Operational Research, Elsevier, vol. 266(1), pages 179-192.
  39. Bolin, David & Wallin, Jonas & Lindgren, Finn, 2019. "Latent Gaussian random field mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 80-93.
  40. Touzani, Samir & Busby, Daniel, 2013. "Smoothing spline analysis of variance approach for global sensitivity analysis of computer codes," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 67-81.
  41. Waley W. J. Liang & Herbert K. H. Lee, 2019. "Bayesian nonstationary Gaussian process models via treed process convolutions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 797-818, September.
  42. Storlie, Curtis B. & Swiler, Laura P. & Helton, Jon C. & Sallaberry, Cedric J., 2009. "Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1735-1763.
  43. Lauric A Ferrat & Marc Goodfellow & John R Terry, 2018. "Classifying dynamic transitions in high dimensional neural mass models: A random forest approach," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-27, March.
  44. Yang, Dazhi & Gueymard, Christian A., 2019. "Producing high-quality solar resource maps by integrating high- and low-accuracy measurements using Gaussian processes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
  45. Debdeep Pati & David Dunson, 2014. "Bayesian nonparametric regression with varying residual density," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(1), pages 1-31, February.
  46. Ray-Bing Chen & Ying-Chao Hung & Weichung Wang & Sung-Wei Yen, 2013. "Contour estimation via two fidelity computer simulators under limited resources," Computational Statistics, Springer, vol. 28(4), pages 1813-1834, August.
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